mvectors

pages/Semantic_Search.py

@@ -801,42 +801,22 @@ def render_answer(answer,index):
                         final_desc_ = "<p></p><p>"
                         for word_ in desc___:
                             str_=re.sub('[^A-Za-z0-9]+', '', word_).lower()
-                            ###### stemming and highlighting
-                        
-                            # ans_text = ans['desc']
-                            # query_text = st.session_state.input_text
-
                             stemmed_word = next(iter(set(stem_(str_))))
-                            # print("stemmed_word-------------------")
-                            # print(stemmed_word)
-                            
-
-                            # common = ans_text_stemmed.intersection( query_text_stemmed)
-                            # #unique = set(document_1_words).symmetric_difference(  )
-
-                            # desc__stemmed = stem_(desc__)
-
-                            #print(str_)
                             if(stemmed_word in res___ or str_ in res___):
                                 if(stemmed_word in res___):
                                     mod_word = stemmed_word
                                 else:
                                     mod_word = str_
-                                #print(str_)
                                 if(res___.index(mod_word)==0):
-                                    #print(str_)
                                     final_desc_ +=  "<span style='color:#ffffff;background-color:#8B0001;font-weight:bold'>"+word_+"</span> "
                                 elif(res___.index(mod_word)==1):
-                                    #print(str_)
                                     final_desc_ +=  "<span style='color:#ffffff;background-color:#C34632;font-weight:bold'>"+word_+"</span> "
                                 else:
-                                    #print(str_)
                                     final_desc_ +=  "<span style='color:#ffffff;background-color:#E97452;font-weight:bold'>"+word_+"</span> "
                             else:
                                 final_desc_ += word_ + " "
                         
                         final_desc_ += "</p><br>"
-                        #print(final_desc_)
                         st.markdown(final_desc_,unsafe_allow_html = True)
                     elif("highlight" in ans and 'Keyword Search' in st.session_state.input_searchType):
                         test_strs = ans["highlight"]

semantic_search/all_search_execute.py

@@ -274,10 +274,6 @@ def handler(input_,session_id):
                 vector_payload['neural']['product_description_vector']['filter']["bool"]["must"].append({"term": {"gender_affinity": st.session_state.input_gender}})
             if(st.session_state.input_price!=(0,0)):
                 vector_payload['neural']['product_description_vector']['filter']["bool"]["must"].append({"range": {"price": {"gte": st.session_state.input_price[0],"lte": st.session_state.input_price[1] }}})
-        
-#         print("vector_payload**************")   
-#         print(vector_payload)    
-        
         ###### end of efficient filter applying #####
         
         hybrid_payload["query"]["hybrid"]["queries"].append(vector_payload)
@@ -310,7 +306,6 @@ def handler(input_,session_id):
             multimodal_payload['neural']['product_multimodal_vector']['filter'] = filter_['filter']
             
         if(st.session_state.input_manual_filter == "True"):
-            print("presence of filters------------")
             multimodal_payload['neural']['product_multimodal_vector']['filter'] = {"bool":{"must":[]}}
             if(st.session_state.input_category!=None):
                 multimodal_payload['neural']['product_multimodal_vector']['filter']["bool"]["must"].append({"term": {"category": st.session_state.input_category}})
@@ -409,14 +404,9 @@ def handler(input_,session_id):
             path = "retail-search-colbert-description/_search" 
             url = host + path
             r = requests.get(url, auth=awsauth, json=hybrid_payload, headers=headers)
-            print(r.status_code)
-            #print(r.text)
             response_ = json.loads(r.text)
-            print("-------------colbert ---- 3-----------")
-            #print(response_)
             docs = response_['hits']['hits']
             docs = cb.search(docs)
-            print("-------------COLBERT------------5------------------------------------------")
         else:
             single_query = hybrid_payload["query"]["hybrid"]["queries"][0]
             del hybrid_payload["query"]["hybrid"]
@@ -525,7 +515,6 @@ def handler(input_,session_id):
             arr.append(res_)
             dup.append(doc['_source']['image_url'])
 
-    #print(arr)
     return arr[0:k_]
     
     

utilities/mvectors.py

@@ -70,8 +70,6 @@ def search(hits):
             token = tokens[index]
             if(token!='[SEP]' and token!='[CLS]'):
                 query_token_vector = np.array(i)
-                print("query token: "+token)
-                print("-----------------")
                 scores = []
                 for m in with_s:
                     m_arr = m.split("-")